Rail infrastructure owners are motivated to minimize staff exposure to unsafe environments and replace the time consuming and subjective process of manual crosstie (track) inspection with objective and automated processes. The motivation is driven by the desire to improve rail safety in a climate of increasing annual rail traffic volumes and increasing regulatory reporting requirements. Objective, repeatable, and accurate track inventory and condition assessment also provide owners with the innovative capability of implementing comprehensive asset management systems which include owner/region/environment specific track component deterioration models. Such rail specific asset management systems would yield significant economic benefits in the operation, maintenance and capital planning of rail networks. A primary goal of such automated systems is the non-destructive high-speed assessment of railway track infrastructure. Track inspection and assessment systems currently exist including, for example, Georgetown Rail (GREX) Aurora 3D surface profile system and Ensco Rail 2D video automated track inspection systems. Such systems typically use coherent light emitting technology, such as laser radiation, to illuminate regions of the railway track bed during assessment operations.
The effect of variations in surface properties of railroad tracks and surrounding surfaces has a significant impact on light levels reflected from these surfaces and subsequently detected by 3D sensors. Reflected light levels entering the sensors are not always optimum due to variations surface color (light or dark colored surfaces) or texture for example. Incorrect lighting levels can cause the 3D track surface profile measured by a 3D sensor to be distorted or imperceptible, affecting the measured profile accuracy.
What is needed, therefore, is a way to control the intensity of light emitters in real time in order to achieve the clearest 3D profiles possible.